CN116827791A

CN116827791A - Network slice resource allocation method, system, equipment and storage medium

Info

Publication number: CN116827791A
Application number: CN202211215767.7A
Authority: CN
Inventors: 李婷婷; 李国辉; 金鹏程
Original assignee: China Mobile Communications Group Co Ltd; China Mobile Suzhou Software Technology Co Ltd
Current assignee: China Mobile Communications Group Co Ltd; China Mobile Suzhou Software Technology Co Ltd
Priority date: 2022-09-30
Filing date: 2022-09-30
Publication date: 2023-09-29

Abstract

The application discloses a network slice resource allocation method, a system, equipment and a storage medium, wherein the method comprises the following steps: acquiring a service request of a first application program in a wireless access network; determining a first slicing strategy under the condition that the first application program triggers a session peak value based on the service request; the first slicing strategy at least comprises the steps of distributing a first number of resource blocks of a second slice corresponding to a second application program in the wireless access network to the first slice corresponding to the first application program; and sending the first slicing strategy to an SDN controller through a north interface of a Software Defined Network (SDN), so that the SDN controller sends the driven first slicing strategy to a slicing scheduler through a south interface of the SDN, and the slicing scheduler allocates resources for each slice in the wireless access network according to the first slicing strategy.

Description

Network slice resource allocation method, system, equipment and storage medium

Technical Field

The present application relates to the field of communications technologies, and in particular, but not limited to, a method, a system, an apparatus, and a storage medium for allocating network slice resources.

Background

Recent advances in the sensor and communication fields open the way for continued evolution of internet of things (Internet of Things, ioT) services where a large number of devices need to access transport networks using widely deployed radio access technologies and radio access networks (Radio Access Network, RAN). The enhanced mobile broadband (Enhanced Mobile Broadband, emmbb) can provide a large bandwidth as one of three applications of 5G (5 th Generation Mobile Communication Technology, fifth generation mobile communication technology). As IoT services may create a large number of short burst sessions, affecting the performance of sharing the same RAN mobile users.

Disclosure of Invention

In view of this, the embodiments of the present application provide a method, a system, a device, and a storage medium for allocating network slice resources.

In a first aspect, an embodiment of the present application provides a method for allocating network slice resources, where the method includes: acquiring a service request of a first application program in a wireless access network; determining a first slicing strategy under the condition that the first application program triggers a session peak value based on the service request; the first slicing strategy at least comprises the steps of distributing a first number of resource blocks of a second slice corresponding to a second application program in the wireless access network to the first slice corresponding to the first application program; and sending the first slice strategy to an SDN controller through a north interface of a Software Defined Network (SDN), so that the SDN controller sends the first slice strategy after driving to a slice scheduler through a south interface of the SDN, and the slice scheduler allocates resources for each slice in the wireless access network according to the first slice strategy.

In a second aspect, an embodiment of the present application provides a network slice resource allocation system, where the system includes: the slice application program is used for acquiring a service request of a first application program in the wireless access network; the slicing application is further configured to determine a first slicing policy based on the service request if it is determined that the first application triggers a session peak; the first slicing strategy at least comprises the steps of distributing a first number of resource blocks of a second slice corresponding to a second application program in the wireless access network to the first slice corresponding to the first application program; an SDN controller, configured to receive the first slicing policy sent by the slicing application through a northbound interface of a software defined network SDN, and drive the first slicing policy; and the slice scheduler is used for receiving the first slice strategy after the driving sent by the SDN controller through the southbound interface of the SDN and distributing resources for each slice in the wireless access network according to the first slice strategy.

In a third aspect, an embodiment of the present application provides an electronic device, including a memory and a processor, where the memory stores a computer program that can be run on the processor, and the processor implements steps in the network slice resource allocation method according to the embodiment of the present application when the processor executes the program.

In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, on which a computer program is stored, where the computer program when executed by a processor implements the steps in the network slice resource allocation method according to the embodiment of the present application.

In the embodiment of the application, the first application program can communicate with the slice application program, the slice application program creates and configures the first slice strategy according to the requirement of the second slice according to the service request of the first application program, the SDN controller drives the first slice strategy and then sends the first slice strategy to the slice scheduler, and the slice scheduler allocates resources, so that the resources of the RAN are efficiently shared between the first application program and the second application program, the first application program and the second application program respectively correspond to different slices (the first slice and the second slice), the negative influence of flow change between the first application program and the second application program is reduced, and the stability and the isolation are ensured; on this basis, once the first application program triggers the session peak, more resource blocks are allocated to the slices of the first application program, so that the network performance of the first application program in the peak time is improved.

Drawings

Fig. 1 is a flow chart of a network slice resource allocation method according to an embodiment of the present application;

FIG. 2 is an interactive schematic diagram of a network slice resource allocation system according to an embodiment of the present application;

FIG. 3 is an interactive schematic diagram of another network slice resource allocation system according to an embodiment of the present application;

FIG. 4 is an interactive schematic diagram of a network slice resource allocation system according to another embodiment of the present application;

fig. 5 is a schematic diagram of a composition structure of a network slice resource allocation system according to an embodiment of the present application;

fig. 6 is a schematic diagram of a hardware entity of an electronic device according to an embodiment of the present application.

Detailed Description

The technical scheme of the application is further elaborated below with reference to the drawings and examples.

Fig. 1 is a flow chart of a network slice resource allocation method according to an embodiment of the present application, as shown in fig. 1, the method may be applied to a slice application program of a network slice resource allocation system, and the method includes the following steps:

step S102: acquiring a service request of a first application program in a wireless access network;

the service request may be that the first application program requests a certain amount of resources for a plurality of users in a specific area, and guarantees a specific quality of service (Quality of Service, qoS) target, which is also called QoS requirement, and the QoS target may include network performance targets such as availability, throughput, delay variation (including jitter and drift), packet loss rate, and the like.

Step S104: determining a first slicing strategy under the condition that the first application program triggers a session peak value based on the service request; the first slicing strategy at least comprises the steps of distributing a first number of resource blocks of a second slice corresponding to a second application program in the wireless access network to the first slice corresponding to the first application program;

wherein, the software defined network (Software Define Network, SDN) changes the Control mode of the traditional network architecture, dividing the network into a Control layer (Control Plane) and a Data layer (Data Plane); network slicing is an on-demand networking manner, which allows operators to separate multiple virtual end-to-end networks on a unified infrastructure, and each network slice is logically isolated from the radio access network to the carrier network and then to the core network to adapt to various types of applications. In one network slice, the method can be divided into at least three parts of a wireless network sub-slice, a bearing network sub-slice and a core network sub-slice.

In the internet of things, a large number of internet of things devices need to use widely deployed wireless access technologies and wireless access networks to access a transmission network; enhanced mobile broadband, one of three applications of 5G, is capable of providing large bandwidths.

The first application and the second application are an enhanced mobile broadband eMBB application or an internet of things IoT application; the eMBB application may be a 4G (4 th Generation Mobile Communication Technology, fourth generation mobile communication technology) application or a 5G application; the first application is the owner of the first slice, the second application is the owner of the second slice, i.e. the owners of the first slice and the second slice may be different IoT applications, different eMBB applications, one may be an IoT application, and the other may be an embbb application; correspondingly, the first slice and the second slice may be an eMBB slice or an IoT slice.

As IoT services may generate a large number of short burst sessions, affecting the performance of mobile users sharing the same RAN, SDN-based network slicing can provide support for heterogeneous service segments sharing the same RAN, including both landscape and portrait heterogeneous demands; the landscape heterogeneous requirements may be heterogeneous requirements between multiple different IoT applications or heterogeneous requirements between multiple different eMBB applications, and the portrait heterogeneous requirements may be heterogeneous requirements between an IoT application and an eMBB application.

Judging whether the first application program triggers a session peak or not under the condition that the service request accords with a service level agreement (Service Level Agreement, SLA), wherein the service level agreement refers to a agreement or contract commonly accepted by two parties between an enterprise providing service and a client in terms of quality, level, performance and the like of the service; the first application triggering a session peak may be understood as the first application approaching the session peak or having a tendency to change towards the session peak before reaching the session peak. The first slicing strategy is also called a dynamic Resource allocation algorithm, and the dynamic Resource allocation algorithm of the slicing application program can be to allocate additional Resource Blocks (RBs) to IoT slices before the session peak of the IoT application program, so as to mitigate the influence of the IoT peak session on the eMBB service performance. It is assumed that once a peak session is triggered, more RBs are allocated to IoT slices, so that IoT performance during peak periods corresponding to the session peaks may be improved, while QoS requirements of 4G or 5G mobile users may be met during other periods.

Step S106: and sending the first slice strategy to an SDN controller through a north interface of a Software Defined Network (SDN), so that the SDN controller sends the first slice strategy after driving to a slice scheduler through a south interface of the SDN, and the slice scheduler allocates resources for each slice in the wireless access network according to the first slice strategy.

In the related art, a control part (processing scheduling decision) and an operation part (responsible for performing scheduling decision) of the MAC layer (Media Access Control, medium access control layer) are combined together. Thus, radio resources are scheduled among multiple services according to a specific scheduling policy implemented by the network operator at the RAN access point, i.e. the eNB, also called eNodeB (Evolved Node B). The proprietary nature of the RAN devices prevents the RAN from adapting to new services such as IoT, and cannot implement new policies in a flexible and efficient manner.

In the embodiment of the present application, first, as shown in fig. 2, the network slice resource allocation system may include a slice application 21, an SDN controller 22 and a slice scheduler 23, where the slice application 21 is also referred to as an SDN slicing application, the SDN controller is also referred to as an SDN slicing controller, the MAC layer includes a control layer and a data layer, and the control layer of the MAC layer is separated by the data layer and is hosted in a centralized SDN controller of a cloud site of the RAN.

The access site eNB of the RAN may be released from control responsibility and process Resource Blocks (RBs) allocation according to scheduling decisions (i.e., the first slicing strategy after driving) made by the SDN controller 22. The eNB is equipped with "proxy" software: slice scheduler 23, slice scheduler 23 is connected to SDN slice controller 22 via southbound interface 24 (SouthBound Interface, SBI). The scheduling decisions are made remotely on the slicing application 21, taking into account the needs of IoT and eMBB services.

Second, the owners of the slices (i.e., ioT applications 201 and 4G/5G applications 202) may communicate service requests to the slicing application 21 of the SDN through northbound interface 25 (NorthBound Interface, NBI). Thus, the SDN slice controller 22 cooperates with the northbound slice application 21 to perform admission control. To this end, the slicing application 21 may verify whether the service request meets a pre-established SLA and may match the required QoS target according to the real-time network status.

Next, the slicing application 21 may build a first slicing strategy. The construction of slicing strategies, i.e. orchestrating deployment, is, for example, from the operator's perspective, roughly divided into the following flows: the user subscribes to communication service in a specific scene, the communication service management function of the slicing application program finishes the conversion from user requirements to SLA, then the slicing management function selects proper sub slices, and the sub slice management function finishes the application of sub slice resources and the life cycle management and deploys various resources of the sub slice resources, so that the use of the communication service is obtained. On the basis of the application, the slices are optimally adjusted to be dynamically allocated.

SDN slice controller 22 communicates with proxy software 23 of the eNB via SBI interface 24. Finally, the slice scheduler in slice scheduler 23 may instantiate slices by reserving the appropriate bandwidth (i.e., number of RBs) for each slice owner according to the slice scheduling policy for each slice owner performed by SDN slice controller 22.

In some embodiments, before determining a first slicing strategy in case it is determined that the first application triggers a session peak based on the service request at step S104", the method further comprises:

Step S1032: determining a ratio between the number of resources allocated to the first slice at each of a plurality of times within a first period of time and the number of resources actually required by the first slice;

wherein the first period is also called a time window, which may be expressed as Δt, and the time window is an application method of a period, and based on a sliding time window, a range of Δt may be defined as [0,120], which is a unit of seconds, and may be used to dynamically adjust a size of each slice; the transmission time interval may be denoted as TTI; the number of resource blocks allocated to a first slice at each time may be expressed as rbs_allowed (TTI, iot), the number of resource blocks actually required by a first slice at each time may be expressed as rbs_required (TTI, iot), and the ratio between the number of resources allocated to the first slice at each time and the number of resources actually required by the first slice may be expressed as rb_r (TTI, s) or rb_r (TTI, iot).

Step S1034: calculating an average of the ratios at the plurality of times;

wherein calculating the average value rb_rΔ (sfiot) of the ratio rb_r (TTI, s) at a plurality of times can be represented by the following formula (1):

RB_R _Δ(sIoT) ＝AVG(RB_R(TTI,sIoT),ΔT) (1)；

step S1036: and under the condition that the average value is smaller than or equal to a first threshold value corresponding to the first application program, determining that the first application program triggers a session peak value.

Wherein a first threshold, also called a critical value, may be set for evaluating the highest or lowest value of an effect if the average value of the first slice is less than or equal to the first threshold, i.e. RB_R _Δ(sIoT) ≤Thr _IOT (sIoT), the slice application may identify a slice (e.g., a second slice) that has a performance above a particular slice threshold (e.g., a second threshold) using an average value of the ratios of other slices (slices other than the first slice) rb_rΔ. If a second slice having a performance above the particular slice threshold is identified, the slice application may transfer a percentage of the bandwidth from the higher performing slice to the worse performing slice, i.e., transfer a percentage of the bandwidth of the second slice having a performance above the particular slice threshold to the first slice having a performance below the particular threshold, and allocate a first number of resource blocks in the second slice to the worse performing first slice using unused resource blocks in the second slice.

Assuming that the first slice is an IoT slice and the second slice is a 4G or 5G slice (i.e., mob slice), at the beginning of the IoT session peak, the value of rb_rΔ (sfiot) will be very low because the number of RBs required for IoT traffic in this TTI is much higher than the number of RBs required for the previous time interval. In practice, a lower rb_rΔ (sfiot) may be used to determine the start of an IoT session peak and trigger the appropriate lateral/longitudinal expansion operation. That is, to meet the requirements of these two slices, it is assumed that once the session peak is triggered, more RBs are allocated to IoT slices, which may improve IoT performance during peak hours.

The IoT and eMBB slice sizes are configured in real-time, taking into account the number of RBs (Resource blocks) actually needed per slice and the number of RBs currently used per slice. To this end, the present application assumes IoT traffic is characterized by periodic session peaks, taking into account traffic profiles to predict peak periods of internet of things traffic. The dynamic allocation algorithm of the "slice application" may be to actively allocate additional RBs to IoT slices prior to peaking to mitigate the impact of IoT peak sessions on the eMBB service performance.

In the embodiment of the application, since the resources actually needed by the application program are much and the allocated resources are less when the application program reaches the session peak value quickly, whether the first application program triggers the session peak value is judged according to the ratio of the resources allocated to the first slice to the resources actually needed by the first slice, and the session peak value is determined according to the average value of the ratio of a plurality of moments, so that whether the first application program triggers the session peak value can be determined more accurately, conveniently and efficiently.

In some embodiments, the step S1034 "calculates an average value of the ratio at a plurality of time instants", including the following steps S10341 and S10342:

Step S10341: determining the weight corresponding to each ratio based on the sequence of the moments; the weight corresponding to the ratio is decreased in a reverse order according to the sequence of the corresponding time;

it should be noted that, the closer the time is to the current time, the more the real demand of the slice on the resource can be reflected, so the selection of the first threshold may be based on a sliding time window, the selection range of time extends to within 1 month, the smaller the weight of the longer-distance data is, and the larger the weight of the closer data is.

Step S10342: an average of the ratios at the plurality of times is calculated based on the ratio at each of the times and the corresponding weights.

The ratio of the time instants and the corresponding weight can be used for weighted average.

In the embodiment of the application, the average value of the ratios of the multiple moments can be further accurately calculated by giving a larger weight to the ratio of the closer moments and a smaller weight to the ratio of the longer moments according to the sequence of the moments.

In some embodiments, the method further comprises:

step S1030: acquiring sensitivity of each first application program in the wireless access network; the sensitivity is used for representing the emergency degree of the resource requirement of the first application program;

Step S1031: determining a first threshold corresponding to each first application program according to the sensitivity of each first application program; the higher the sensitivity of the first application program is, the larger the first threshold value corresponding to the first application program is; the first threshold is used for judging whether the first application program triggers a session peak.

The first threshold value of the different scenes is different to a certain extent, and for the delay-sensitive application program, namely the application program with high sensitivity, the first threshold value is higher than the first threshold value of the common application program, because for the sensitive application scene, once the first application program corresponding to the first slice identifies the second slice with higher performance, unused resource blocks of the second slice must be reasonably scheduled immediately; the selection of the percentage of the scheduled resource blocks is linearly transferred according to the sum of all bandwidth values of the slice application.

In the embodiment of the application, the application program with higher sensitivity is enabled to trigger the peak session more easily by setting the first threshold value with higher sensitivity, so that the resource transfer is performed immediately when the peak session is triggered, and the flexibility and convenience of the resource transfer are improved.

In some embodiments, the method further comprises:

step 108: determining a second slicing strategy under the condition that the session peak of the first application program is determined to be ended based on the service request; the second slicing strategy includes at least allocating a second number of resource blocks of the first slice to the second slice;

the pseudo code of the dynamic slicing algorithm provided by the embodiment of the application is as follows, assuming that the first slice is an IoT slice and the second slice is a Mob slice:

algorithm: ioT dynamic slicing

Setting siot=iot slice

Setting sMob= Mobile Traffic slice

The method comprises the following steps:

wherein, referring to the algorithm, if the average value RB_Rdelta (sIoT) of the ratio is smaller than or equal to Thr _IOT (sIoT) a second number (% Size (sIoT)) of resource blocks may be rolled out of the Mob slice, and from the rolled out second number of resource blocks, the first number (% Size (sMob) [ TTI) required for the IoT slice is rolled out]) Is transferred to the IoT slice.

If the average RB_Rdelta (sIoT) of the ratio is greater than Thr _IOT (sIoT) may determine that a session peak of the first application ends, and may transfer a second number of resource blocks from IoT slices to Mob slices.

Step 110: and sending the first slice strategy to the SDN controller through a north interface of the SDN, so that the SDN controller sends the second slice strategy after driving to the slice scheduler through a south interface of the SDN, and the slice scheduler allocates resources for each slice in the wireless access network according to the second slice strategy.

The second slicing strategy is the same as the first slicing strategy, and can be sent to an SDN controller through a north interface of a Software Defined Network (SDN), so that the SDN controller sends the second slicing strategy after driving to a slicing scheduler through a south interface of the SDN, and the slicing scheduler allocates resources for each slice in the radio access network according to the second slicing strategy.

In the present embodiment, it is assumed that once a session peak is triggered, more RBs are allocated to IoT slices, while unused RBs are reallocated to mobile users during other time intervals (e.g., after the session peak is over). The additionally allocated RBs will be used to hold other video frames in the buffer, preserving the quality of the video streaming operation during IoT peak times. In this way, ioT performance during peak hours can be ensured on the one hand, and QoS requirements of mobile users can be met on the other hand.

In some embodiments, the service request carries network performance requirements, "determining a first slicing strategy" in step 104 includes:

step 1041a: the first slicing strategy is determined based on the network performance requirements and the network performance of the radio access network.

In some embodiments, the first slicing strategy further comprises a total number of resource blocks used by each of the slices, a duration of each of the slices, and a network performance index for each of the slices.

Wherein, the slices can be allocated to owners of the slices by setting three parameters of size, duration of the slices and network performance index (QoS target), mainly the reorganization of resources, virtual and physical resources needed for meeting QoS target selection: the size indicates the total number of RBs (resource blocks) that will be used for the tile. The duration of a slice is expressed in the number of Transmission Time Intervals (TTI). QoS targets refer to network performance metrics (e.g., throughput targets, etc.) required to aggregate traffic on-chip.

The slice application program may compare the network performance requirement in the service request with the actual network performance of the radio access network to determine the resources actually allocated to each slice, and the QoS target required by the first slice may be matched according to the real-time network state if the network performance requirement is higher than the actual network performance, and may be matched according to the network performance requirement if the network performance requirement is lower than the actual network performance.

In some embodiments, the service request is for requesting autonomous configuration of a slicing strategy, and the determining the first slicing strategy includes:

step 1041b: acquiring slice configuration operation performed by a user on a user interface of the slice application program;

step 1042b: the first slicing strategy is determined based on the slicing configuration operation.

As shown in fig. 3, the network slice resource allocation system includes a slice application 31, an SDN controller 32, and a slice scheduler 33, where the slice application 31 and the SDN controller 32 may be connected through a north interface NBI 35, and the SDN controller 32 and the slice scheduler 33 may be connected through a south interface SBI; the slice scheduler 33 may be implemented by RRU 331 (Remote Radio Unit ), RCC 332 (Radio Cloud Center, wireless cloud center) and EPC 333 (Evolved Packet Core,4G core network), the RRU 331 may be implemented by Dell OPTIPLEX 7010, the RCC 332 may be implemented by HP ZBook G3, and the network virtualization platform in the HP ZBook G3 may be VMware Ubuntu VM; the RRU 332 is connected to the base station 36 (USRP B210) via a USB3.0 interface, the base station 36 is connected to the IoT node 301 or the mobile smart phone (4G/5G node, also called user equipment) 302, any user can configure the slicing process in real time via the GUI (Graphical User Interface ) 37 of the Web (World Wide Web), through the slicing application 31, the user can test the slicing solution, and manually set the size of each slice for testing. In addition, the configuration of the slicing process may also be accomplished automatically using dynamic slicing algorithms in the slicing application.

In the embodiment of the application, the slicing strategy can be configured by a user independently, and the slicing strategy can be automatically and completely configured by a dynamic slicing algorithm, so that the flexibility of slicing strategy configuration can be improved.

As the conventional "one-shot" architecture fails to meet a range of heterogeneous requirements of the RAN. This places higher demands on supporting IoT in the RAN. In view of this, the design of 5G has a programmable and flexible infrastructure, and network slicing is one of the most promising design approaches, capable of providing optimal support for heterogeneous service segments sharing the same RAN. The solutions in the related art are as follows:

emerging network virtualization technologies, such as software defined networking SDN, change the Control mode of traditional network architectures, separating networks into Control layers (Control planes) and Data layers (Data planes). SDN has three mainstream implementations, openFlow organization-dominated open source software, application-centric infrastructure (APPlication Centric Infrastructure, ACI), and NSX, a network virtualization platform that can filter traffic going and going in a hypervisor.

Network function virtualization (Network Functions Virtualization, NFV), proactively provides network services that typically run on proprietary hardware that owns virtual machines, where virtual machines are understood to emulate the operating system of the proprietary hardware. With NFV, network components of individual slices are virtualized to meet specific needs.

SDN virtualization has the following problems:

SDN focuses on network programmability, which is a programming capability of a bottom layer, is not flexible and convenient enough, cannot cope with various service applications in different scenes, and particularly cannot solve differentiated services in an eMBB service scene.

In combination with the new form of 5G sharing construction, although the problem of efficient management is met to a certain extent, SDN ignores the problem of sharing of different application service RAN radio access networks, and does not meet the requirement of generality.

SDN does not pay attention to the problem of resource allocation, and resource utilization shortage or resource overload exists in the static allocation of resources in the network slices, so that it is very necessary to dynamically adjust the resource quantity of the network slices, and realize dynamic on-demand allocation of the resources so as to optimize the utilization rate of the network resources.

The present application is an SDN based network slice solution that enables flexible spectrum sharing (i.e., resource sharing) among multiple slices. While ensuring isolation between them. The 5G network fully utilizes the fusion with the SDN virtualization architecture, realizes dynamic resource allocation on demand for the IoT under the condition of large bandwidth mobile access eMBB service, provides differentiated services, and can meet diversified QoS (Quality of Service ) requirements.

As shown in fig. 4, it is assumed that there are two types of devices: ioT node (IoT application) 401 and mobile smartphone (4G/5G node) 402.IoT node 401 is connected to the RAN through 5G gateway 46, which includes access sites and cloud sites, the access sites including slice scheduler 43, which slice scheduler 43 may be implemented by RRU 431, RCC 432, and EPC 433. IoT gateways periodically collect IoT data and when the collected data needs to be delivered to the cloud, ioT node 401 establishes a connection with the C-RAN (Cloud Radio Access Network ) network through NBI 45. The C-RAN network is composed of an SDN architecture, which is a centralized SDN controller 42, where the SDN controller 42 is connected to a slice scheduler 43 through an SBI 44, and considers a global view of the network state provided by the SDN paradigm in real time, and processes the slicing process in real time. The slicing process is performed in a northbound "slicing application" 41, which consists of two different modules, one for each traffic class. The first module, called "IoT application" 401, stores IoT-related traffic information, such as traffic profiles of IoT devices, including estimated times of session peaks, information about the traffic profiles can be obtained through a RAN information base, i.e., a database containing various user performance metrics. The second module, called the "4G/5G application" 402, is used to analyze mobile traffic to determine the amount of resources needed to meet the mobile user QoS (Quality of Service) requirements. Finally, the "slice application" 41 determines the amount of resources to be allocated to each slice while ensuring QoS of the entire system, taking into account the traffic profile of each slice.

The present application implements the slicing procedure in an SDN-based manner according to policies employed in the "slicing application" for enabling dynamic slicing of radio resources between IoT and eMBB (Enhanced Mobile Broadband) services.

The present application aims to qualitatively evaluate an SDN based slice solution to evaluate in real time a centralized resource slice allocation algorithm in an SDN controller. To this end, a northbound "slicing application" prototype is presented to enable any user to configure the slicing process in real-time via a Web GUI (Graphical User Interface ), as shown in fig. 3. With the "slice application," the user can test the slice solution and manually size each slice for testing. In addition, the configuration of the slicing process can also be automatically completed by utilizing a dynamic slicing algorithm.

The IoT and eMBB slice sizes are configured in real-time, taking into account the number of RBs (Resource blocks) actually needed per slice and the number of RBs currently used per slice. To this end, the present application assumes IoT traffic is characterized by periodic session peaks, taking into account traffic profiles to predict peak periods of internet of things traffic.

The dynamic allocation algorithm of the "slice application" may be to actively allocate additional RBs to IoT slices prior to peaking to mitigate the impact of IoT peak sessions on the eMBB service performance. The main steps of the algorithm are given below:

step S1: resource allocation is an important issue for wireless networks, while satisfaction refers to the careful usage experience of users when using a wireless network after allocating a given resource to them, and the slicing is extended laterally or longitudinally according to satisfaction, for example, adding a new machine to the original web, mail system, which is the lateral extension. This is an architectural concept for the primary user to display the scalability of the system, scaling each slice according to its resource allocation satisfaction, denoted by rb_r (TTI, s), to represent the ratio between the number of RBs allocated (rbs_allowed (TTI, s iot)) and the number of RBs actually required for that particular TTI slice (rbs_required (TTI, s iot)).

Step S2: average value rb_rΔ(s) (rb_r) of rb_r (TTI, s) calculated in time window Δt _Δ(sIoT) =avg (rb_r (TTI, sfiot), Δt), the time window is an application method of the period, the present application defines the range of Δt as [0,120 ] based on a sliding time window]In seconds, which is used to dynamically resize each slice.

Step S3: setting a threshold, also called critical value, for evaluating the highest or lowest value of an effect if the average value of the first slice is less than or equal to the first threshold (RB_R _Δ(sIoT) ≤Thr _IOT (sIoT)), then the "slice application" would utilize rb_rΔ of other slices (other than the first slice) to identify slices with performance above a particular slice threshold (second threshold). If a slice with performance above the particular slice threshold is identified (second slice), the "slice application" will transfer a percentage of the bandwidth from the second slice to another slice with poor performance (e.g., the first slice), i.e., transfer a percentage of the bandwidth of the second slice with performance above the particular slice threshold to the first slice with performance below the particular threshold, utilize unused RBs in the second slice, and assign them to the first slice with poor performance.

The selection of the specific threshold value is also based on a sliding time window, but the selection range of time extends to 1 month or less, and the more distant data is weighted smaller, the more closely the time weight is weighted larger. Meanwhile, the threshold selection of different scenes has a certain difference, and for delay-sensitive applications, the specific threshold is higher than that of common applications, because for sensitive application scenes, once slicing applications recognize the threshold with higher performance, unused RBs must be reasonably scheduled immediately; the percentage selection is linearly transferred based on the sum of all bandwidth values of the slice application.

At the beginning of the IoT session peak, the value of rb_rΔ(s) will be very low, since the number of RBs required for IoT traffic in this TTI is much higher than the number of RBs required for the previous time interval. In practice, a lower rb_rΔ(s) may be used to determine the start of an IoT session peak and trigger the appropriate lateral/longitudinal expansion operation. That is, to meet the requirements of these two tiles, it is assumed that once the session peak is triggered, more RBs are allocated to IoT slices while unused RBs are reallocated to mobile users in other time intervals. The additionally allocated RBs will be used to hold other video frames in the buffer, preserving the quality of the video streaming operation during IoT peak times. In this way, ioT performance during peak hours can be ensured on the one hand, and QoS requirements of mobile users can be met on the other hand.

The present application proposes a network slicing method for sharing bandwidth resources between IoT and eMBB slices, which utilizes a slice scheduling algorithm driven by a centralized SDN controller. Conventional LTE (Long Term Evolution ) scheduler operations are converted into SDN-based solutions, where the control layers of the MAC layer (Media Access Control, medium access control layer) are separated by data layers and hosted in a centralized SDN controller at the cloud site, which solution is executed at the northbound application.

In the conventional architecture, the control part (processing scheduling decisions) and the operation part (responsible for performing scheduling decisions) of the MAC are combined together. Thus, radio resources are scheduled among multiple services according to a specific scheduling policy implemented by the network operator at the RAN access point, i.e. the eNB (eNodeB). The proprietary nature of the RAN devices prevents the RAN from adapting to new services such as IoT, and cannot implement new policies in a flexible and efficient manner. The present application aims to generate an effective network slicing strategy in a more flexible scheduling method by using SDN.

The embodiment of the application provides a design of a northbound SDN application program, which can create and configure an IoT slice as required while considering the eMBB service requirement; network slicing solutions based on SDN can realize efficient sharing of RAN resources between eMBB and IoT services, and guarantee isolation.

Embodiments of the present application exploit the 5G flexible infrastructure to propose a software defined radio (Software Defined Radio, SDR) prototype that allows different services (IoT and eMBB) to share the same Radio Access Network (RAN) while guaranteeing quality of service (QoS) and Service Level Agreements (SLA). The method has universality.

The embodiment of the application efficiently shares the RAN resources among various services (the IoT and the eMBB) and can provide isolation among different slice segments, thereby reducing the negative influence of traffic variation between the IoT and the eMBB services and ensuring the stability of the system.

The embodiment of the application manages the creation and configuration of the slice in a dynamic manner, configures the slice according to a predefined input set as required, pays attention to the resource allocation problem, and provides a dynamic slice method aiming at verifying isolation properties, which is a key driving force of effective slicing.

It should be noted that, in the embodiment of the present application, if the above-mentioned network slice resource allocation method is implemented in the form of a software function module, and is sold or used as a separate product, the network slice resource allocation method may also be stored in a computer readable storage medium. Based on such understanding, the technical solution of the embodiments of the present application may be embodied essentially or in a part contributing to the related art in the form of a software product stored in a storage medium, including several instructions for causing an electronic device (which may be a mobile phone, a tablet computer, a desktop computer, a personal digital assistant, a navigator, a digital phone, a video phone, a television, a sensing device, etc.) to perform all or part of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read Only Memory (ROM), a magnetic disk, an optical disk, or other various media capable of storing program codes. Thus, embodiments of the application are not limited to any specific combination of hardware and software.

Based on the foregoing embodiments, the embodiments of the present application provide a network slice resource allocation system, where the system includes each module included, and may be implemented by a processor in a device; of course, the method can also be realized by a specific logic circuit; in practice, the processor may be a central processing unit (CPU, central Processing Unit), a microprocessor (MPU, microprocessor Unit), a digital signal processor (DSP, digital Signal Processing), or a field programmable gate array (FPGA, field Programmable Gate Array), or the like.

Fig. 5 is a schematic structural diagram of a network slice resource allocation system according to an embodiment of the present application, as shown in fig. 5, the system 500 includes a slice application 501, an SDN controller 502, and a slice scheduler 503, where:

the slicing application 501 is configured to obtain a service request of a first application in a radio access network;

the slicing application 501 is further configured to determine, based on the service request, a first slicing policy if it is determined that the first application triggers a session peak; the first slicing strategy at least comprises the steps of distributing a first number of resource blocks of a second slice corresponding to a second application program in the wireless access network to the first slice corresponding to the first application program;

The SDN controller 502 is configured to receive the first slicing policy sent by the slicing application 501 through a northbound interface of a software defined network SDN, and drive the first slicing policy;

the slice scheduler 503 is configured to receive the first slice policy after driving sent by the SDN controller 502 through a southbound interface of the SDN, and allocate resources for each slice in the radio access network according to the first slice policy.

In some embodiments, the slicing application 501 is further configured to determine, at a plurality of times within a first period, a ratio between an amount of resources allocated to the first slice at each of the times and an amount of resources actually required by the first slice; calculating an average of the ratios at the plurality of times; and under the condition that the average value is smaller than or equal to a first threshold value corresponding to the first application program, determining that the first application program triggers a session peak value.

In some embodiments, the slicing application 501 is further configured to determine a weight corresponding to each of the ratios based on the order of the multiple moments; the weight corresponding to the ratio is decreased in a reverse order according to the sequence of the corresponding time; an average of the ratios at the plurality of times is calculated based on the ratio at each of the times and the corresponding weights.

In some embodiments, the slicing application 501 is further configured to obtain a sensitivity of each of the first applications in the radio access network; the sensitivity is used for representing the emergency degree of the resource requirement of the first application program; determining a first threshold corresponding to each first application program according to the sensitivity of each first application program; the higher the sensitivity of the first application program is, the larger the first threshold value corresponding to the first application program is; the first threshold is used for judging whether the first application program triggers a session peak.

In some embodiments, the slicing application 501 is further configured to determine a second slicing policy based on the service request if it is determined that a session peak of the first application is over; the second slicing strategy includes at least allocating a second number of resource blocks of the first slice to the second slice; transmitting the first slicing strategy to the SDN controller through a north interface of the SDN so that the SDN controller can transmit the second slicing strategy after driving to the slicing scheduler through a south interface of the SDN;

The slice scheduler 503 is configured to allocate resources for each slice in the radio access network according to the second slice policy.

In some embodiments, the SDN controller 502 is configured to receive the second slicing policy sent by the slicing application 501 through a northbound interface of a software defined network SDN and drive the second slicing policy;

the slice scheduler 503 is further configured to receive the second slice policy after driving, which is sent by the SDN controller 502 through a southbound interface of the SDN.

In some embodiments, the service request carries a network performance requirement, and the slicing application 501 is further configured to determine the first slicing policy based on the network performance requirement and a network performance of the radio access network.

In some embodiments, the service request is used for requesting autonomous configuration of a slicing strategy, and the slicing application 501 is further used for acquiring slicing configuration operations performed by a user at a user interface of the slicing application; the first slicing strategy is determined based on the slicing configuration operation.

The description of the system embodiments above is similar to that of the method embodiments above, with similar benefits as the method embodiments. For technical details not disclosed in the system embodiments of the present application, please refer to the description of the method embodiments of the present application for understanding.

Correspondingly, an embodiment of the present application provides a device, fig. 6 is a schematic diagram of a hardware entity of an electronic device according to an embodiment of the present application, as shown in fig. 6, where the hardware entity of the electronic device 600 includes: comprising a memory 601 and a processor 602, said memory 601 storing a computer program executable on the processor 602, said processor 602 implementing the steps in the network slice resource allocation method of the above embodiments when said program is executed.

The memory 601 is configured to store instructions and applications executable by the processor 602, and may also cache data (e.g., image data, audio data, voice communication data, and video communication data) to be processed or processed by the processor 602 and the modules in the device 600, which may be implemented by a FLASH memory (FLASH) or a random access memory (Random Access Memory, RAM).

Correspondingly, an embodiment of the present application provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the steps in the network slice resource allocation method provided in the above embodiment.

It should be noted here that: the description of the storage medium and the device embodiments above is similar to that of the method embodiments above, with similar benefits as the device embodiments. For technical details not disclosed in the embodiments of the storage medium and the method of the present application, please refer to the description of the embodiments of the apparatus of the present application.

It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. It should be understood that, in various embodiments of the present application, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application. The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.

The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.

Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read Only Memory (ROM), a magnetic disk or an optical disk, or the like, which can store program codes. Alternatively, the above-described integrated units of the present application may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the embodiments of the present application may be embodied essentially or in a part contributing to the related art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a mobile phone, a tablet computer, a desktop computer, a personal digital assistant, a navigator, a digital phone, a video phone, a television, a sensing device, etc.) to perform all or part of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a removable storage device, a ROM, a magnetic disk, or an optical disk.

The methods disclosed in the method embodiments provided by the application can be arbitrarily combined under the condition of no conflict to obtain a new method embodiment. The features disclosed in the several product embodiments provided by the application can be combined arbitrarily under the condition of no conflict to obtain new product embodiments. The features disclosed in the embodiments of the method or the apparatus provided by the application can be arbitrarily combined without conflict to obtain new embodiments of the method or the apparatus.

The foregoing is merely an embodiment of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of network slice resource allocation, performed by a slice application, the method comprising:

acquiring a service request of a first application program in a wireless access network;

determining a first slicing strategy under the condition that the first application program triggers a session peak value based on the service request; the first slicing strategy at least comprises the steps of distributing a first number of resource blocks of a second slice corresponding to a second application program in the wireless access network to the first slice corresponding to the first application program;

And sending the first slice strategy to an SDN controller through a north interface of a Software Defined Network (SDN), so that the SDN controller sends the first slice strategy after driving to a slice scheduler through a south interface of the SDN, and the slice scheduler allocates resources for each slice in the wireless access network according to the first slice strategy.

2. The method according to claim 1, wherein the method further comprises:

determining a ratio between the number of resources allocated to the first slice at each of a plurality of times within a first period of time and the number of resources actually required by the first slice;

calculating an average of the ratios at the plurality of times;

and under the condition that the average value is smaller than or equal to a first threshold value corresponding to the first application program, determining that the first application program triggers a session peak value.

3. The method of claim 2, wherein said calculating an average of said ratios at said plurality of times comprises:

determining the weight corresponding to each ratio based on the sequence of the moments; the weight corresponding to the ratio is decreased in a reverse order according to the sequence of the corresponding time;

An average of the ratios at the plurality of times is calculated based on the ratio at each of the times and the corresponding weights.

4. A method according to claim 3, characterized in that the method further comprises:

acquiring sensitivity of each first application program in the wireless access network; the sensitivity is used for representing the emergency degree of the resource requirement of the first application program;

determining a first threshold corresponding to each first application program according to the sensitivity of each first application program; the higher the sensitivity of the first application program is, the larger the first threshold value corresponding to the first application program is; the first threshold is used for judging whether the first application program triggers a session peak.

5. The method according to any one of claims 1 to 4, further comprising:

determining a second slicing strategy under the condition that the session peak of the first application program is determined to be ended based on the service request; the second slicing strategy includes at least allocating a second number of resource blocks of the first slice to the second slice;

and sending the first slice strategy to the SDN controller through a north interface of the SDN, so that the SDN controller sends the second slice strategy after driving to the slice scheduler through a south interface of the SDN, and the slice scheduler allocates resources for each slice in the wireless access network according to the second slice strategy.

6. The method according to any of claims 1 to 4, wherein the service request carries network performance requirements, or wherein the service request is used for requesting autonomous configuration of slicing policies;

the determining a first slicing strategy includes:

determining the first slicing strategy based on the network performance requirement and the network performance of the radio access network; or alternatively, the process may be performed,

acquiring slice configuration operation performed by a user on a user interface of the slice application program; the first slicing strategy is determined based on the slicing configuration operation.

7. The method of any of claims 1-4, wherein the first slicing strategy further comprises a total number of resource blocks used per the slice, a duration of each of the slices, and a network performance index for each of the slices.

8. A network slice resource allocation system, the system comprising:

the slice application program is used for acquiring a service request of a first application program in the wireless access network;

the slicing application is further configured to determine a first slicing policy based on the service request if it is determined that the first application triggers a session peak; the first slicing strategy at least comprises the steps of distributing a first number of resource blocks of a second slice corresponding to a second application program in the wireless access network to the first slice corresponding to the first application program;

An SDN controller, configured to receive the first slicing policy sent by the slicing application through a northbound interface of a software defined network SDN, and drive the first slicing policy;

and the slice scheduler is used for receiving the first slice strategy after the driving sent by the SDN controller through the southbound interface of the SDN and distributing resources for each slice in the wireless access network according to the first slice strategy.

9. An electronic device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that the processor implements the steps of the network slice resource allocation method of any one of claims 1 to 7 when the program is executed.

10. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor realizes the steps in the network slice resource allocation method according to any one of claims 1 to 7.